Social Urban Networks

PhD Positions to work with my team at the Network Science Institute, Northeastern University The Social Urban Networks (SUN) group, led by Dr. Esteban Moro, focuses on developing computational social science tools to address urban challenges, from climate change and inequality to health and economic development. By using large datasets of human behavior, tools and ideas from physics, applied mathematics, complex systems or network science, and collaborations with industry, government, and local communities, we seek not only to advance the understanding of the temporal dynamics of social systems to unprecedented levels but also to transform our findings into tools and policies to help achieve resilient and equitable adaptation of our societies. ...

Postdoc Positions to work with my team at the Network Science Institute, Northeastern University: The Network Science Institute is seeking researchers at the postdoctoral and associate levels to join the new Social Urban Networks (SUN) group. The Social Urban Networks (SUN) group, led by Dr. Esteban Moro, focuses on developing computational social science tools to address urban challenges, from climate change and inequality to health and economic development. By using large datasets of human behavior, tools and ideas from physics, applied mathematics, complex systems or network science, and collaborations with industry, government, and local communities, we seek not only to advance the understanding of the temporal dynamics of social systems to unprecedented levels but also to transform our findings into tools and policies to help achieve resilient and equitable adaptation of our societies. ...

I am thrilled to announce that I will be joining the Network Science Institute at Northeastern University as a Professor starting January 2024! As a researcher in Social Urban Networks (SUN) it is a dream come true. My group will focus on developing computational social science tools to address urban challenges, from climate change, inequality to health and economic development. By using large datasets of human behavior, tools and ideas from physics, applied mathematics, complex systems or network science, and collaborations with industry, government, and local communities, we seek not only to advance the understanding of the temporal dynamics of social systems to unprecedented levels but also to transform our findings into tools and policies to help achieve resilient and equitable adaptation of our societies. ...

Authors: Yan Leng , Xiaowen Dong, Esteban Moro, Alex Pentland Publication: Information Systems Research, Articles in Advance 21 Jun (2023) LINK Abstract: We use high-resolution mobile phone data with geolocation information and pro- pose a novel technical framework to study how social influence propagates within a phone communication network and affects the offline decision to attend a performance event. Our fine-grained data are based on the universe of phone calls made in a European country between January and July 2016. ...

Authors: Yanni Yang, Alex Pentland, Esteban Moro Publication: EPJ Data Science 12, Article number: 15 (2023) LINK Abstract: Urbanization and its problems require an in-depth and comprehensive understanding of urban dynamics, especially the complex and diversified lifestyles in modern cities. Digitally acquired data can accurately capture complex human activity, but it lacks the interpretability of demographic data. In this paper, we study a privacy-enhanced dataset of the mobility visitation patterns of 1. ...

Authors: Takahiro Yabe, Bernardo García Bulle Bueno, Xiaowen Dong, Alex Pentland & Esteban Moro Publication: Nature Communications volume 14, Article number: 2310 (2023) LINK Abstract: Diversity of physical encounters in urban environments is known to spur economic productivity while also fostering social capital. However, mobility restrictions during the pandemic have forced people to reduce urban encounters, raising questions about the social implications of behavioral changes. In this paper, we study how individual income diversity of urban encounters changed during the pandemic, using a large-scale, privacy-enhanced mobility dataset of more than one million anonymized mobile phone users in Boston, Dallas, Los Angeles, and Seattle, across three years spanning before and during the pandemic. ...